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Adaptive closed-loop deep brain stimulation method and device and electronic equipment

A deep brain stimulation, adaptive technology for medical electronic systems

Active Publication Date: 2022-01-18
FUDAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide an adaptive closed-loop deep brain stimulation method, device and electronic equipment, which can effectively solve the problem of personality under multi-state and long-term conditions. neuromodulation problem

Method used

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  • Adaptive closed-loop deep brain stimulation method and device and electronic equipment
  • Adaptive closed-loop deep brain stimulation method and device and electronic equipment
  • Adaptive closed-loop deep brain stimulation method and device and electronic equipment

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Embodiment

[0056] Such as Figure 1~3 As shown, the present embodiment provides an adaptive closed-loop deep brain stimulation method, comprising the following steps:

[0057]S1. Perform parameter search through Particle Swarm Optimization (PSO) to obtain target proportional-derivative-integral controller parameters to determine the target proportional-derivative-integral controller.

[0058] PSO is a random search algorithm based on group cooperation developed by simulating the foraging behavior of birds, which can be used to solve optimization problems. Each bird is abstracted as a "particle" in the parameter space, and the position of the food is abstracted as a feasible solution that meets the requirements. All particles have a fitness value determined by the function being optimized, and the velocity of each particle determines the direction and distance of their parameter search, which is updated after each generation of calculation. In the iterative process, the particles search...

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Abstract

The invention discloses an adaptive closed-loop deep brain stimulation method and device and electronic equipment. The method comprises the steps: carrying out parameter searching through a particle swarm optimization algorithm to obtain a target proportional-differential-integral controller parameter so as to determine a target proportional-differential-integral controller; carrying out deep brain simulation by adopting stimulation parameters obtained through the target proportional-differential-integral controller; and while carrying out deep brain simulation, carrying out online correction on parameters of the target proportional-differential-integral controller. The method can achieve effects of automatically calculating a gain of the PID controller for different patients and automatically calibrating the gain of the PID controller along with the change of the states of the patients so as to implement personalized nerve regulation and control under the multi-state and long-time-history conditions.

Description

technical field [0001] The invention relates to the field of medical electronic systems, in particular to an adaptive closed-loop deep brain stimulation method, device and electronic equipment. Background technique [0002] Abnormal neural activity in the brain can lead to a variety of neurological and psychiatric diseases. Deep brain stimulation (deepbrain stimulation, DBS) is currently a clinically feasible treatment, especially for patients who are ineffective in drug therapy. [0003] At present, the continuous open-loop stimulation mode is used clinically, and the doctor adjusts the stimulation parameters according to the patient's condition and fixes them until the next visit. Stimulation parameters include stimulation amplitude, frequency, and pulse width. In the open-loop stimulation mode, the stimulation parameters cannot be properly adjusted according to the patient's instantaneous or long-term state changes, and long-term continuous stimulation may also bring abo...

Claims

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Application Information

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IPC IPC(8): A61N1/36A61B5/388
CPCA61N1/3606A61N1/36082A61N1/36103A61N1/36128A61N1/36139A61B5/388
Inventor 权昭宇王守岩刘伟
Owner FUDAN UNIV
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